Making MRIs Faster with AI

Facebook and New York University have published fastMRI, a dataset of 1.5 million magnetic resonance images (MRI) of the knee, to accelerate the development of AI that can reduce the time it takes to complete an MRI scan. The NYU School of Medicine collected the 1.5 million images from 10,000 MRI scans. The data could help researchers develop AI that can piece together images from MRI scans for a complete scan, thereby reducing the number of images and time needed to perform MRI scans, which can take up to 30-45 minutes.

Michael McLaughlin is a research assistant at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.